Underwater localization using single beacon measurements: Observability analysis for a double integrator system

Palma, Daniela De; Arrichiello, Filippo; Parlangeli, Gianfranco; Indiveri, Giovanni

doi:10.1016/j.oceaneng.2017.07.025

Cited by 37 publications

(14 citation statements)

References 27 publications

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“…De Palma et al (2017) address observability for the single beacon navigation problem of an UV using a nonlinear, kinematic “double integrator” model with acceleration as the model input and range to a stationary beacon as the output. The observability analysis addresses two complementary issues: the local weak observability for the nonlinear system, and, similar to Parlangeli and Indiveri (2014), the global observability for a LTV representation of the system derived through a state augmentation method.…”

Section: Literature Review: Uv Navigationmentioning

confidence: 99%

Cooperative acoustic navigation of underwater vehicles without a DVL utilizing a dynamic process model: Theory and field evaluation

Harris

Whitcomb

2021

Journal of Field Robotics

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This paper reports the theoretical development and at‐sea field evaluation of a novel combined underwater acoustic communication and navigation system, known as cooperative acoustic navigation (CAN), for underwater vehicles (UVs) utilizing a second‐order dynamic plant model of the submerged UVs. The present state‐of‐the‐art in CAN is to utilize one‐way travel‐time acoustic modem telemetry together with purely kinematic, constant‐velocity plant process models. We term this approach CAN‐KIN. At present, CAN‐KIN is utilized with an on‐board bottom‐lock Doppler velocity log (DVL) providing frequent, high‐accuracy velocity corrections. However, DVLs are relatively expensive, have significant power requirements, can be physically large, and have limited acoustic bottom‐lock range, which restricts their use to a maximum of 25–420 m above the sea floor. In this study, we investigate the utility of a second‐order dynamic UV plant process model in CAN of UVs equipped with an acoustic modem, attitude, and depth sensors, but lacking a DVL, and a surface ship equipped with an acoustic modem and global positioning system. We term CAN utilizing a dynamic model CAN‐DYN. This paper reports results from at‐sea field trials conducted in the Chesapeake Bay with the Johns Hopkins University Iver3 UV. These experimental results indicate the submerged UV position estimate from CAN‐KIN is poor and even unstable in the absence of DVL velocity observations. These field experimental results also show that CAN‐DYN performs well without a DVL. Our results suggest CAN‐DYN without a DVL does not exhibit instability as does CAN‐KIN without a DVL, performs similarly to CAN‐KIN with a DVL, and outperforms DVL‐based dead reckoning. Additionally, we report an experimental evaluation of the effect of adding (relative) velocity corrections in the form of acoustic range‐rate observations to CAN utilizing a dynamic model without a DVL. We conclude that the addition of infrequent velocity observations, such as those provided by acoustic range rate, does not appear to improve the performance of CAN‐DYN without a DVL.

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Section: Literature Review: Uv Navigationmentioning

confidence: 99%

Cooperative acoustic navigation of underwater vehicles without a DVL utilizing a dynamic process model: Theory and field evaluation

Harris

Whitcomb

2021

Journal of Field Robotics

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“…The challenges of dealing with single range measurements come from the fact that they are a non-linear algebraic map of the vehicles' positions hence the observability analysis requires the tools of local and weakly local observability (Hermann and Krener, 1977 ), but this approach suffers from several difficulties (Gadre and Stilwell, 2004 ; Ross and Jouffroy, 2005 ; Jouffroy and Reger, 2006 ). However, an alternative approach has been recently investigated recurring to a reformulation of the problem, which requires the observability of a linear time varying system (see, e.g., Batista et al, 2011 ; De Palma et al, 2017 ) so that a number of useless drawbacks of the local approach are avoided.…”

Section: Introductionmentioning

confidence: 99%

Control Protocols for Range-Based Navigation of a Networked Group of Underwater Vehicles

Palma

Indiveri²,

Parlangeli

2020

Front. Robot. AI

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This paper tackles the problem of formation reconstruction for a team of vehicles based on the knowledge of the range between agents of a subset of the participants. One main peculiarity of the proposed approach is that the relative velocity between agents, which is a fundamental data to solve the problem, is not assumed to be known in advance neither directly communicated. For the purpose of estimating this quantity, a collaborative control protocol is designed in order to mount the velocity data in the motion of each vehicle as a parameter through a dedicated control protocol, so that it can be inferred from the motion of the neighbor agents. Moreover, some suitable geometrical constraints related to the agents' relative positions are built and explicitly taken into account in the estimation framework providing a more accurate estimate. The issue of the presence of delays in the transmitted signals is also studied and two possible solutions are provided explaining how it is possible to get a reasonable range data exchange to get the solution both in a centralized fashion and in a decentralized one. Numerical examples are presented corroborating the validity of the proposed approach.

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“…Indeed, the research of robotic navigation in two-dimensional space has achieved great results and extended to the study of multirobot systems [8], while during underwater navigation, AUVs cannot rely on Global Navigation Satellite Systems (GNSSs) due to the attenuation of electromagnetic radiation in the water domain, and in the absence of specific positioning systems, they can exclusively relay on dead-reckoning techniques. As the latter approaches integrate noisy and biased measurements from Inertial Measurement Units (IMUs) and velocity sensors, they suffer from numerical drift that makes them usable only for relatively short periods [9]. And the inertial navigation system (INS) is also mostly applied on AUVs, but INS usually suffers from error accumulation.…”

Section: Introductionmentioning

confidence: 99%

“…More recently, research efforts focused on position systems based on the use of range measurements to a single node with the aim of developing the solutions which is simple, cheap, and easy to operate. Such approaches, known in the literature as single beacon localization [9], single range localization [10], or range-only localization [11], are based on the fusion of range measurements to the single source with information from AUV's onboard sensors as Inertial Measurement Unit (IMU), Doppler Velocity Logger (DVL), and depth sensors.…”

Section: Introductionmentioning

confidence: 99%

A Single-Way Ranging Localization of AUVs Based on PSO of Outliers Elimination

Fan

et al. 2018

Journal of Robotics

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Localization of autonomous underwater vehicles (AUVs) is a very important and challenging task for the AUVs applications. In long baseline underwater acoustic localization networks, the accuracy of single-way range measurements is the key factor for the precision of localization of AUVs, whether it is based on the way of time of arrival (TOA), time difference of arrival (TDOA), or angle of arrival (AOA). The single-way range measurements do not depend on water quality and can be taken from long distances; however, there are some limitations which exist in these measurements, such as the disturbance of the unknown current velocity and the outliers caused by sensors and errors of algorithm. To deal with these problems, an AUV self-localization algorithm based on particle swarm optimization (PSO) of outliers elimination is proposed, which improves the performance of angle of arrival (AOA) localization algorithm by taking account of effects of the current on the positioning accuracy and eliminating possible outliers during the localization process. Some simulation experiments are carried out to illustrate the performance of the proposed method compared with another localization algorithm.

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Underwater localization using single beacon measurements: Observability analysis for a double integrator system

Cited by 37 publications

References 27 publications

Cooperative acoustic navigation of underwater vehicles without a DVL utilizing a dynamic process model: Theory and field evaluation

Cooperative acoustic navigation of underwater vehicles without a DVL utilizing a dynamic process model: Theory and field evaluation

Control Protocols for Range-Based Navigation of a Networked Group of Underwater Vehicles

A Single-Way Ranging Localization of AUVs Based on PSO of Outliers Elimination

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